Identification of mahogany sliced veneer using handheld near-infrared spectroscopy device and multivariate data analysis

IAWA Journal ◽  
2021 ◽  
pp. 1-12
Author(s):  
Hugo S. Rocha ◽  
Jez W.B. Braga ◽  
Daniele C.G.C. Kunze ◽  
Vera T.R. Coradin ◽  
Tereza C. M. Pastore

Abstract The illegal logging of valuable tree species is mainly motivated by a global market that consumes logs, lumber, veneers, and furniture. The use of objective techniques to identify species and the effects of international initiatives such as CITES rules contributes to controlling trade, exploitation, and smuggling of these products. The anatomical identification of wood veneers is limited due to the loss of several anatomical characters in the production process of the veneers. For this reason, we propose the Near-Infrared Spectroscopy technique associated with chemometric tools for the discrimination of wood veneer of woods with similar general characters: Swietenia macrophylla King (mahogany), Carapa guianensis Aubl. (andiroba), Cedrela odorata L. (cedro), Micropholis venulosa Pierre (curupixá), and Hymenaea coubaril L. (jatobá) using a portable spectrometer.The development of the discrimination models was performed using the PLS-DA (Partial Least Squares for Discriminant Analysis) algorithm. The detection and subsequent exclusion of outliers were performed based on Hotelling T2, Q residuals, and errors in estimating class values. The PLS-DA models showed an efficiency between 96.5% and 100% in the samples’ discrimination among the five forest species. In conclusion, the portable NIRS technology and the PLS-DA models were suitable for the rapid identification and discrimination of the wood veneers.

Holzforschung ◽  
2011 ◽  
Vol 65 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Tereza Cristina Monteiro Pastore ◽  
Jez Willian Batista Braga ◽  
Vera Terezinha Rauber Coradin ◽  
Washington Luiz Esteves Magalhães ◽  
Esmeralda Yoshico Arakaki Okino ◽  
...  

Abstract Mahogany is one of the most valuable woods and was widely used until it was included in Appendix II of the Convention on International Trade in Endangered Species as endangered species. Mahogany wood sometimes is traded under different names. Also, some similar woods belonging to the Meliaceae family are traded as “mahogany” or as being of a “mahogany pattern”. To investigate the feasibility of the use of near infrared spectroscopy for wood discrimination, the mahogany (Swietenia macrophylla King.), andiroba or crabwood (Carapa guianensis Aubl.), cedar (Cedrela odorata L.), and curupixá (Micropholis melinoniana Pierre) woods were examined. Four discrimination models based on partial least squares-discriminant analysis were developed based on a calibration set composed of 88 samples and a test set with 44 samples. Each model corresponds to the discrimination of a wood species from the others. Optimization of the model was performed by means of the OPUS® software followed by statistical analysis software (Matlab®). The observed root mean square errors of predictions were 0.14, 0.09, 0.12, and 0.06 for discriminations of mahogany, cedar, andiroba, and curupixá, respectively. The separations of the species obtained based on the difference in the predicted values was at least 0.38. This makes it possible to perform safe discriminations with a very low probability of misclassifying a sample. This method can be considered accurate and fast.


IAWA Journal ◽  
2011 ◽  
Vol 32 (2) ◽  
pp. 285-296 ◽  
Author(s):  
Jez Willian Batista Braga ◽  
Tereza Cristina Monteiro Pastore ◽  
Vera Teresinha Rauber Coradin ◽  
José Arlete Alves Camargos ◽  
Allan Ribeiro da Silva

Near infrared spectroscopy (NIRS) has been shown effective as a tool for identifying Swietenia when tested as laboratory-processed powder, but testing such powdered wood is not readily adaptable to the fieldidentification of wood. This study explored the efficacy of a fiber optic NIRS scan of solid wood surfaces to separate Swietenia macrophylla King, Carapa guianensis Aubl., Cedrela odorata L., and Micropholis melinoniana Pierre. Transverse, radial, and tangential surfaces were scanned to determine if the surface from which data were collected influenced the spectra recorded. Surfaces were scanned before and after removing the oxidized surface layer of the blocks to test effects of exposure on the spectra. Partial least squares for discriminant analysis models were developed for each taxon separately, based on a calibration set composed of at least 67 samples and a test set with at least 45 samples. The anatomical surface scanned, but not the presence of an oxidized layer, influenced the spectra for each species, necessitating the comparison of the same planes of section. The discriminant models showed small errors for each species, indicating that reliable identifications can be made with NIRS of solid wood surfaces in these species.


PLoS ONE ◽  
2015 ◽  
Vol 10 (8) ◽  
pp. e0134521 ◽  
Author(s):  
Carla Lang ◽  
Flávia Regina Capellotto Costa ◽  
José Luís Campana Camargo ◽  
Flávia Machado Durgante ◽  
Alberto Vicentini

Lipids ◽  
2015 ◽  
Vol 50 (7) ◽  
pp. 705-718 ◽  
Author(s):  
Hormoz Azizian ◽  
Magdi M. Mossoba ◽  
Ali Reza Fardin-Kia ◽  
Pierluigi Delmonte ◽  
Sanjeewa R. Karunathilaka ◽  
...  

2017 ◽  
Vol 25 (5) ◽  
pp. 324-329 ◽  
Author(s):  
Li Dan ◽  
Wu Yi-Hui

The aim of this research was to investigate the feasibility of Fourier transform near infrared spectroscopy combined with chemometric analysis to develop a rapid method for identification of different resin types which had been deemed similar by a preliminary visual examination. Principal component analysis was applied on spectral data to classify two types of epoxy resin samples and three types of phenolic resin samples. In this case, a total of two hundred and fifteen samples were used for the evaluation and validation of two types of epoxy resin samples (SY1342 and SY1346) and three types of phenolic resin samples (Y3567, Y2705 and Y2137). All were correctly differentiated by their respective models. Moreover, in the external validation, the prediction rate of samples correctly classified was also 100%. Such classifications are very important for the detection of adulterated samples and for quality control. Near infrared spectroscopy was shown to be a very reliable, accurate and useful tool to classify resin samples in a fast, clean and inexpensive way compared to classical analysis, and it will enable copper clad laminate manufacturers to detect and take early corrective actions that will ultimately save time and money while establishing a uniform quality.


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